Top 3 Reasons Why Consumers are Rejecting Autonomy

Top 3 reasons why consumers are rejecting autonomy

By: Greg Swando, Senior Research Director


This one word is the beginning of the current automobile industry’s disruption, as OEMs across the world race to incorporate various levels of autonomy and services into their vehicles.  New features such as Forward Collision Warning, Lane Keeping Assistance, and Emergency Braking, among others, have been emerging on the market and becoming more commonplace across vehicle portfolios and advertising campaigns.

But what exactly do consumers think about these new Automated Driver Assistance Systems (ADAS)?

While today’s consumers will see more advances in vehicle technology over the next five years than in the past 50, their rate of technology adoption may be slower to respond, as found by the report “A Consumer-Centric Journey Towards Autonomy”. This report was developed by our automotive team in partnership with SBD and Gamivation, in order to understand the opportunities and challenges that lie ahead in the journey toward next generation autonomous vehicles.

Our report revealed that there are 3 main reasons consumers are not only nervous about the new ADAS features, but may also be rejecting them entirely:

  1. Today’s driver assistance systems are being underutilized and/or misunderstood
  2. A significant number of current ADAS owners find the technology distracting and even irritating
  3. Many consumers reject needing any assistance–and are against giving up control of their vehicle

These and other surprising insights were revealed through the study, including how consumers are viewing the implementation and use of current ADAS features in vehicles. The types of consumers most open and receptive to these features, and those who are more likely to be suspicious or frightened by the new technology, are also revealed in the report, along with why consumers are reacting in these ways.

Our Automotive team and partners will help you learn how your competitors are implementing autonomous features and compare and contrast consumer viewpoints among each of these systems. After determining these points, our team can map out best-practice guidelines to differentiate your features as part of your overall brand, and help to make the consumers’ transition to autonomous features a smoother ride.

To find out more about “A Consumer Centric Journey Towards Autonomy” click here.


Google/Apple Have Little Impact on Consumer Interest in Autonomous Vehicles


By: Mike Scott, Marketing Director; Sara Beauchaine, Marketing Associate

Would you trust an autonomous vehicle? More importantly, would you purchase an autonomous vehicle today?

Technology giants Google and Apple have strong brands and are among the most recognized companies in the world. Yet even when these brands are attached to questions asked of consumers about autonomous vehicles, our January Omnibus revealed that consumers are not only hesitant about “trusting” autonomous vehicles, but about purchasing them as well.

This shouldn’t come as a surprise. There are various stages of progress that will need to occur long before consumers would be comfortable taking a “cat nap” while their self-driving vehicle transports them from point A to point B. At this point, there is a curiosity that consumers have around the topic but not a clear understanding of what defines “autonomous.”

Officially, Apple hasn’t announced that it is in the autonomous vehicle business, but Google has. Our recent Morpace Omnibus found that a total of 31 percent of consumers “somewhat” trust or “completely” trust an autonomous vehicle with Google technology. Another 31 percent don’t trust the technology, leaving the largest percentage–38 percent–undecided.

In addition, only a minority of consumers are willing to purchase an autonomous vehicle at this time. Price could be a factor, but it’s likely that trust plays a role in the answers we received as well. Overall, 58 percent are “unlikely” or “extremely unlikely” to purchase an autonomous vehicle with Google technology, compared to 59 percent for an autonomous vehicle with Apple technology.

Finally, there was little separation between the price consumers are willing to pay for autonomous vehicles powered by Google versus Apple. Eight-in-ten consumers are not willing to pay more than $40,000, which is the base price for some higher-end standard powertrain SUVs in today’s market. The average price most consumers are willing to pay is less than $28,000, with virtually no difference in the median value for Apple versus Google autonomous vehicles.

As it turns out, we may have found one thing that the powerful brands of Google and Apple can’t directly impact—consumers’ perceptions on autonomous vehicles. Discussions and media reports surrounding autonomous vehicles are becoming more prevalent, and it is clear that education needs to be developed before a majority of consumers feel comfortable enough to drive or purchase a “self-driving” vehicle.

There is a long learning curve ahead for consumers before the autonomous technology “war” among the industry giants, not to mention the automotive OEMs, can begin in earnest.


In A Driverless Car Accident, Who’s to Blame?

Traffic on multiple lane highway with motion blur

By: Michael Schmall, Vice President; Sara Beauchaine, Marketing Associate

As we quickly approach the cusp of driverless cars in the automobile industry, autonomous vehicles are being tested on public roads across the country. These cars, such as Google’s self-driving car, are being tested on roads where they interact with human drivers. Mistakes are bound to happen, but what happens when a test goes awry?

Take, for instance, the recent accident in California involving one of Google’s autonomous vehicles. A routine test was being run on a public road when the Google car ran into a public transportation bus as it attempted to get around some sandbags that were lying in the street. The accident occurred at low speeds for both vehicles, 2 mph for the self-driving car and 15 mph for the bus, and no one was injured.

There is a human driver present during testing in Google’s self-driving cars, as in this case, and they are able to take control of the vehicle. Google described their driver’s thought process during this accident in the following excerpt:

“Our test driver, who had been watching the bus in the mirror, also expected the bus to slow or stop. And we can imagine the bus driver assumed we were going to stay put. Unfortunately, all these assumptions led us to the same spot in the lane at the same time. This type of misunderstanding happens between human drivers on the road every day…[We] clearly bear some responsibility, because if our car hadn’t moved there wouldn’t have been a collision. That said, our test driver believed the bus was going to slow or stop to allow us to merge into the traffic, and that there would be sufficient space to do that.”

Even though liability still may not be assigned in this case, as the damage was so limited and both parties may not pursue the responsibility concept, there could soon be thousands of self-driving cars on the road, and we will need to know: Who’s to blame in a driverless car accident?

When it comes to assigning fault in an accident between a self-driving car and non-autonomous car, the answer isn’t clearly distinguished. Because self-driving cars have been involved in very few accidents, none of which were the driverless car’s fault, there isn’t yet a precedent for who is responsible when a self-driving car causes the accident.

So who’s to blame when a driverless car causes an accident? The human in the autonomous vehicle? The automated car manufacturer? The company who created the autonomous technology? Or simply the human operating the non-autonomous car? What about when a driverless car injures a pedestrian – who will be the responsible party in that case?

Depending on the situation and its many variables, the entity liable when a driverless car causes an accident is different in each scenario.

Who—or what—garners the liability is a complicated question, one that depends on the situation at hand, and one that needs solid answers as autonomous technology in vehicles continues to advance. Google’s self-driving car colliding with the bus is the first time a driverless car caused an accident. This concept may not be fully legally defined or even understood for many years after self-driving vehicles hit the road.

So, when approaching the question: “In a driverless car accident, who’s to blame?”— we aren’t quite sure yet.


Your Car Might be Watching You in the Near Future

Eye viewing digital information. Conceptual image.

By: Michael Schmall, Vice President; Sara Beauchaine, Marketing Associate

Google, Apple, Tesla, and leading car manufacturers around the world are well on their way to producing autonomous vehicles, with the expectation that some of these cars will be on dealership lots within the next 10 years.

Autonomous qualities are already being incorporated in vehicles, and, for example, can be seen in Tesla’s products as “Autopilot”. This technology utilizes multiple sensors, radar, cameras, and sonar to pick up on road lane lines and other vehicles, allowing the car to essentially drive itself on expressways. This technology requires the driver to—at the very least—keep one finger on the wheel.

With advancements in technology such as “Autopilot” leading the way, a logical question looms on the horizon: Will artificial intelligence eventually come into the equation of manufacturing vehicles to be completely autonomous?

Artificial intelligence has been around for years, and within reach of consumers. It can be seen in Apple’s Siri, GPS units, and many other devices. Automotive companies like Toyota are now investing heavily in artificial intelligence, and technology tinkerers are attempting to bolster autonomous cars’ driving abilities with this technology.

One of these tinkerers is George Hotz. 26-year-old Hotz not only built a self-driving car in his garage by himself, but is also programming it with artificial intelligence—rather than manually coded technology. According to a recent article, Hotz revealed that incorporating artificial intelligence software in self-driving cars will help avoid the common roadblocks currently experienced by other autonomous test vehicles.

Some of the common obstacles currently facing manually coded autonomous technology, like the Google car, include:

  • Human hand signals (such as those from an officer directing traffic)
  • Small animals crossing the road (larger living creatures, such as deer and jaywalkers, are sensed by the car)
  • Bad weather (snow, fog, and splashing ground water interferes with how the car receives and interprets information)
  • Areas with no cell signal (operation ceases without a connection to a cell signal, as critical access to GPS maps is cut off)

Hotz believes that some of these obstacles can be avoided by employing “deep-learning techniques in autonomous technology”.

Artificial intelligence software, like what Hotz is producing, watches the driver’s behavior. It learns as it observes how certain situations are typically handled by the human driver, and then makes its own decisions by mimicking these learned behaviors and actions when operating autonomously.

If artificial intelligence can truly be utilized for autonomous vehicles, we may soon find solutions to some of the issues that need to be resolved before these cars can be introduced to the market. There is a possibility that soon, cars might be watching you, too!